SAN FRANCISCO, June 7, 2018—Sight Machine Inc. today introduced FactoryTX Edge and FactoryTX Cloud, the only enterprise-grade edge and cloud data acquisition solutions purpose-built for manufacturing. The new tools enable rapid deployment and centralized management of multi-factory IoT data ingestion. They give manufacturers the flexibility to acquire machine data from both production facilities and the cloud, and to efficiently prepare the data for manufacturing analytics.

FactoryTX Edge and FactoryTX Cloud are built to address the specific data acquisition challenges faced by manufacturers. They have three core functions: Collect, Transform, and Transmit, enabling them to aggregate data from disparate factory devices or cloud-based data lakes, pre-process it, and securely stream it to Sight Machine’s cloud-based analytics software. These offerings give customers flexibility in determining where data processing takes place.

FactoryTX Edge and FactoryTX Cloud help manufacturers rapidly deploy and extend manufacturing analytics applications throughout their enterprise.They normalize industrial data from disparate systems into a standardized format and securely transmit it to Sight Machine’s platform.

FactoryTX Edge includes rapid self-service installation technology that allows customers to remotely deploy digital manufacturing applications to facilities using their own IT and operations teams. It enables remote provisioning, monitoring and maintenance to accelerate the ability to deploy, scale, and continuously improve digital manufacturing capabilities. Browser-based configuration tools allow companies to scale up and add more data sources as their projects expand. FactoryTX Edge also provides a platform for custom, low-latency edge analytics for manufacturers that want this capability.

“The right combination of cloud, private network and edge computing resources will vary depending on corporate policies, the type of factory equipment used and the specific needs of the projects under development,” said Jon Sobel, CEO of Sight Machine. “Sight Machine FactoryTX Edge makes the edge enterprise-ready, with an easy-to-deploy, easy-to-manage solution that lets manufacturers select the best mix of local and cloud processing for each location and use case.”

FactoryTX Cloud offers the same major functions as FactoryTX Edge but is optimized to run in the cloud. FactoryTX Cloud is for manufacturers that are already moving their manufacturing data to the cloud, enabling them to quickly turn this aggregated data into insights.

“In order to keep up with the rapid advances in big data analytics technologies, to gain multi-factory visibility and to enable enterprise scalability, most manufacturers will turn to secure cloud-based solutions,” said Sight Machine Chief Technical Officer Nate Oostendorp. “Sight Machine FactoryTX Edge and FactoryTX Cloud help our customers securely acquire production data from multiple sources regardless of where it resides.”

FactoryTX Edge and FactoryTX Cloud help manufacturers rapidly deploy and extend manufacturing analytics applications throughout their enterprises. These offerings lower the cost and increase the speed of scaling digital manufacturing capabilities across multiple plants, while avoiding the risk of creating new data and application silos in the process.

About Sight Machine

Sight Machine is powering the digital transformation of manufacturing, used by Global 500 companies to make better, faster decisions about their operations. Sight Machine’s analytics platform, purpose-built for discrete and process manufacturing, uses artificial intelligence, machine learning and advanced analytics to help address critical challenges in quality and productivity throughout the enterprise. Sight Machine is optimized to run on the major cloud platforms including AWS, Google Cloud Platform, and Microsoft Azure.

Daya Vivek is Director, Platform Engineering at Sight Machine. She has a a 20 year track record in delivering enterprise software products and engaging customers to meet diverse market and user needs. Previously, Daya had 17 year career at IBM spanning multiple roles: an Engineering Manager for the Watson Discovery Service hosted on the IBM cloud, a Solution Architect for the Customer Enablement team for IBM’s Big Data Solution (Infosphere Biginsights), and a software developer in pureQuery (a data access platform for database clients) and IBM’s database engine DB2. Daya has a Master’s in Computer Science from Arizona State University and an MBA from Santa Clara University.

Josh Brown

DevOps Engineering Manager

Josh Brown is an Engineering Manager focusing on infrastructure and tooling for Sight Machine. For the last 15 years, Josh has worked to help scale multiple startups across many different industries, from fashion to mobile messaging. Josh uses his experience from previous startups to solve nuanced problems that span well beyond the implementation of technology.

In his personal life, Josh has also been involved in multiple humanitarian efforts, in Mexico and Haiti, and enjoys exploring the world with his family.

Ed Jimenez

VP of Marketing

Ed Jimenez is VP of Marketing for Sight Machine. Previously, Mr. Jimenez led Cisco’s Enterprise and Industry Marketing teams. He also worked as a senior consultant helping Cisco’s largest customers understand how disruptive technologies affect the customer experience. Prior to joining Cisco, Mr. Jimenez led Gartner’s Retail & Consumer Products Practice. He also spent a number of years in the retail and manufacturing industries with positions in technology transformation and operations.

Mr. Jimenez has published a number of papers on retail & manufacturing technology trends and was a regular host for the NBC Morning News Technology Report.

Mr. Jimenez earned his M.B.A. from the University of Illinois.

Harry Wornick

Director of Product

Harry Wornick is the Director of Product for Sight Machine. For the past several years, Mr. Wornick has led Sight Machine’s product efforts, from infrastructure and data pipeline, to visualization and analytics. Previously, Mr. Wornick was the Senior Product Manager at Support.com, leading the development of cloud-based customer support software.

Mr. Wornick earned his B.S. in Engineering from Harvey Mudd College, where he spent several years working with national laboratories on renewable energy research.

Ajay Nayak

Product Engineering Manager

Ajay Nayak is the Product Engineering Manager for Sight Machine. Previously, he was VP of Engineering for Bakround, a startup focused on improving the recruiting process for hiring managers and candidates using machine learning. Prior to that, he led an engineering team for Insightly, an SMB-focused CRM. He also has consulting experience at Booz Allen Hamilton and Slalom, which has enabled him to gain expertise in process improvement for a variety of industries.

Ajay has a BS in Electrical & Computer Engineering from Rutgers University, and an MEng in Systems Engineering from Stevens. He’s passionate about using technology to measurably improve societal outcomes and is actively involved in youth-oriented volunteering for his local community.

Kurt DeMaagd, PhD

Chief AI Officer & Co-Founder

Kurt co-founded Slashdot.org and has served as a professor at Michigan State University in information management, economics, and policy. Kurt is an accomplished analytics programmer.

Chris Dobbrow

SVP, Sales

Chris has over 25 years of strategic enterprise sales experience creating & executing successful go to market strategies focused on enterprise customers. He has served in senior management roles at Perforce Software, SourceForge and Ziff-Davis.

Jon Sobel

CEO & Co-Founder

Jon has served on the management teams of several companies in pioneering industries, including Tesla Motors, SourceForge, and in its early years, Yahoo! Jon holds an BA from Princeton, a JD from the University of Michigan, and an MBA from Wharton.

Adam Taisch

VP of Global Sales & Co-Founder

Adam has led business development, product development and sales in innovative industries for 15 years. An early employee at Yahoo!, and a proud son of the Midwest, Adam excels at ensuring the new technologies serve client needs.

Anthony Oliver

Lead Applications Engineer & Co-Founder

Anthony has over 12 years of experience developing and deploying robotics, computer vision, and data analysis tools in the manufacturing sector. He is a multidisciplinary software engineer who is equally at home in application engineering, dev-ops, front and back end development, and vision programming.

Jerry Wu

CFO

Jerry has over 20 years of experience in technology corporate finance and public/private equity investments. Prior to his career in finance he was a manufacturing engineer with Silicon Graphics. Jerry holds BS and MS degrees in electrical engineering from Stanford and an MBA from Wharton. He is a CFA charterholder.

John Stone

VP of Business Development & Partnerships

An experienced business development executive who has worked with global brands to drive engagement, collaboration, and results across organizations at all levels.

Beth Crane

VP of Data

Beth Crane, PhD is Vice President of Data for Sight Machine, the category leader in manufacturing analytics. In this role she focuses on helping manufacturers understand how advanced analytical techniques can solve complex problems in production and operations.

Prior to Sight Machine, Beth has worked in both academia and industry and has led the development of analytical and reporting tools used for continuous process improvement.

She received her PhD and Masters of Science degrees from the University of Michigan and was awarded a National Science Foundation postdoctoral fellowship to explore the development of statistical methods for predicting dysfunction in multi-dimensional time series data.

Sudhir Arni

VP of Implementation

Sudhir Arni​ is Sight Machine’s VP of Manufacturing Transformation. Prior to joining Sight Machine, Sudhir was an engagement manager at McKinsey & Co., where he designed and led manufacturing transformation programs for pharmaceutical and chemical manufacturers. He received joint MBA and Master of Science degrees from the Kellogg School of Management and McCormick School of Engineering at Northwestern University.

Nathan Oostendorp

CTO & Co-Founder

Nathan Oostendorp is the CTO of Sight Machine, he co-founder the company in 2011. Nathan started his career as a controls engineer at Donnelly Corporation (now Magna Mirror) where he worked on PLC programming, computer vision, data acquisition, and robotics for a major automotive supplier.

In 1996 he co-founded Slashdot.org, a major tech news blog which was the center of the Linux and Open Source Software movement. During this period he spun off several other successful open online communities including Everything2.com (an early precursor to Wikipedia) and PerlMonks.org, the central hub for the Perl programming Language. He also created the first Open Source advertising and analytics platform. He then joined SourceForge.net as the site architect and ushered it through a period of growth where it became a top 100 website globally, and hosted several hundred thousand software projects.

He holds a BS in Computer Science from Hope College in Holland Michigan, and an MSI in Information Science from the University of Michigan.

10 Hot AI-powered IoT startups

The Internet of Things generates a lot of data that needs to be processed, and innovative startups recognize that artificial intelligence can lighten the load. Jeff Vance of Network World selected Sight Machine as a 10 hot AI-powered IoT startup. Read on to learn more about what Sight Machine does to address this.

Problem Sight Machine solves: Manufacturers struggle to make optimum decisions quickly. When dealing with problems that emerge on the plant floor, any indecision or delay in decision making could be costly.

In manufacturing, data variety (due to thousands of sources) is far greater than in other IoT use cases, and according to research from Morgan Stanley, the sheer quantity of data is also larger than anywhere else. Traditional analytics tools can’t cope with either the variety or volume.

How they solve it: Sight Machine software uses canonical data models and AI to ingest, integrate, and map massive amounts of heterogeneous data into operational models. The canonical data models represent any machine, line, facility, supplier, part or batch that the manufacturer specifies. Once modeled, data is then systematically and continuously analyzed.

By standardizing the manufacturing models and following a data-first approach to decision making, Sight Machine enables manufacturers to automate data ingestion in a rapid, highly repeatable manner. The standardized model allows manufacturers to create downstream applications that immediately leverage the modeled data.

Analytical techniques include advanced inferential statistics, machine learning and AI, all of which are applied to generate manufacturing-specific insights. Within its platform, Sight Machine analyzes and visualizes data, so results can be viewed via a browser on any connected device.

Why they’re a hot startup to watch: Sight Machine has the deepest pockets in this roundup, backed by $50 million in VC funding. CEO and co-founder Jon Sobel was previously with Tesla and Yahoo, while co-founder and CTO Nathan Oostendorp and co-founder and Chief Data Scientist Kurt DeMaagd previously co-founded Slashdot.org. Finally, the customers Sight Machine has accumulated are impressive, including GE, Fiat Chrysler, and Fujitsu.

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